Journal
FRONTIERS IN CELL AND DEVELOPMENTAL BIOLOGY
Volume 9, Issue -, Pages -Publisher
FRONTIERS MEDIA SA
DOI: 10.3389/fcell.2021.740487
Keywords
lung adenocarcinoma; nuclear mitochondrial genes; risk score; overall survival; signature
Categories
Funding
- National Natural Science Foundation of China [81802282]
- Natural Science Foundation of Shandong Province [ZR2020MH233]
- Jinan Science and Technology Development Program [201907112]
- Clinical Medicine Technology and Innovations Plan of Jinan City [201907066]
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This study identified 18 nuclear mitochondrial genes (NMGs) associated with the prognosis of lung adenocarcinoma (LUAD) and established a risk signature to effectively distinguish high- and low-risk patients. The predictive capacity of the signature was validated in three independent gene expression omnibus (GEO) cohorts. Patients with high-risk NMGs signature showed a significantly lower prevalence of actionable EGFR alterations but accompanied with a more inflame immune tumor microenvironment.
Background: Lung cancer is the leading cause of cancer-related death worldwide, of which lung adenocarcinoma (LUAD) is one of the main histological subtypes. Mitochondria are vital for maintaining the physiological function, and their dysfunction has been found to be correlated with tumorigenesis and disease progression. Although, some mitochondrial-related genes have been found to correlate with the clinical outcomes of multiple tumors solely. The integrated relationship between nuclear mitochondrial genes (NMGs) and the prognosis of LUAD remains unclear. Methods: The list of NMGs, gene expression data, and related clinical information of LUAD were downloaded from public databases. Bioinformatics methods were used and obtained 18 prognostic related NMGs to construct a risk signature. Results: There were 18 NMGs (NDUFS2, ATP8A2, SCO1, COX14, COA6, RRM2B, TFAM, DARS2, GARS, YARS2, EFG1, GFM1, MRPL3, MRPL44, ISCU, CABC1, HSPD1, and ETHE1) identified by LASSO regression analysis. The mRNA expression of these 18 genes was positively correlated with their relative linear copy number alteration (CNA). Meanwhile, the established risk signature could effectively distinguish high- and low-risk patients, and its predictive capacity was validated in three independent gene expression omnibus (GEO) cohorts. Notably, a significantly lower prevalence of actionable EGFR alterations was presented in patients with high-risk NMGs signature but accompanied with a more inflame immune tumor microenvironment. Additionally, multicomponent Cox regression analysis showed that the model was stable when risk score, tumor stage, and lymph node stage were considered, and the 1-, 3-, and 5-year AUC were 0.74, 0.75, and 0.70, respectively. Conclusion: Together, this study established a signature based on NMGs that is a prognostic biomarker for LUAD patients and has the potential to be widely applied in future clinical settings.
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